13 accepted papers
Facial Expression Recognition (FER) is crucial for understanding human emotions, with applications spanning from mental health assessment to marketing recommendation systems. However, existing camera-based methods raise privacy concerns, while RF-based approaches suffer from limited environmental ge…
Inertial tracking is vital for autonomous robots and has gained popularity with the ubiquity of low-cost Inertial Measurement Units (IMUs) and deep learning-powered tracking algorithms. Existing works, however, have not fully utilized IMU measurements, particularly magnetometers, nor maximized the p
We introduce OctoNet, a large-scale, multi-modal, multi-view human activity dataset designed to advance human activity understanding and multi-modal learning. OctoNet comprises 12 heterogeneous modalities (including RGB, depth, thermal cameras, infrared arrays, audio, millimeter-wave radar, Wi-Fi, I…
Predicting blood glucose levels is fundamental for precise primary care of type-1 diabetes (T1D) patients. However, it is challenging to predict glucose levels accurately, not to mention the early alarm of adverse events (hyperglycemia and hypoglycemia), namely the minority class. In this paper, we…
Localization is critical to numerous applications. The performance of classical localization protocols is limited by the specific form of distance information and suffer from considerable ranging errors. This paper foresees a new opportunity by utilizing the exceptional property of entangled quantum…
Indoor maps are essential to indoor location-based services, but are not widely accessible despite considerable efforts from the industry. Existing solutions employ costly hardware to achieve accurate mapping, or resort to laborious crowdsourcing methods, which may suffer from low accuracy due to in…
Heat-stroke and death of children being left alone in a parked car has attracted more and more attentions. As a result, car manufactures start to reward solutions for in-car Child Presence Detection (CPD) system to save lives recently. However, most of the existing works rely on dedicated sensors an…
Speech enhancement and separation have been a long-standing problem with recent advances using a single microphone. With the help of video modality, improvements have been shown for these tasks. In this work, we explore a multimodal approach using mmWave radio devices, as these devices can measure v…
Heart Rate Variability (HRV), which measures the fluctuation of heartbeat intervals, has been considered as an important indicator for general health evaluation. In this paper, we present mmHRV, a contact-free HRV monitoring system using commercial millimeter-wave (mmWave) radio. We devise a heartbe…
With the proliferation of smart devices, voice interfaces have become an integral part of our lives, which typically senses sound by microphones through converting the changes in air pressure into electrical signals. Sound sensing through another modality can enable various sensing applications in t…
Fall detection systems based on WiFi signals are gaining popularity recently. However, most of the existing works relying on training are environment-dependent. In this paper, we propose DeFall, a novel WiFi-based environment-independent fall detection system by leveraging the features inherently as…
Heading direction information is crucial to many ubiquitous computing applications. The main stream has been resorting to inertial sensors, such as accelerometer, gyroscope and magnetometer, which suffer from severe accumulative errors or large degradations indoors. In this paper, we utilize the rad…
Accurate monitoring of human vital signs (e.g. breathing and heart rates) is crucial in detecting medical problems. In this paper, we propose ViMo, a calibration-free remote Vital sign Monitoring system that can simultaneously monitor multiple users by leveraging the channel impulse response (CIR) o…